MSc Environmental Modelling and Data Analysis
University of Bristol · England · MSC-ENVIRONMENTAL-MODELLING-AND-1kdirbr
MSc Environmental Modelling and Data Analysis is a Postgraduate taught degree at University of Bristol, England. It covers areas like data science, mathematical economics, statistical computing, computational mathematics, quantitative economics, data analytics. The summary below is compiled from public course information — approximate, not official.
University of Bristol
Postgraduate taught
What you'll study in MSc Environmental Modelling and Data Analysis
Example subjects: Advanced Project for Chemistry with Scientific Computing, Advanced Environmental Life Chemistry, Advanced Chemical Models and Prediction, Applied Data Science (Teaching Unit), Applied Data Science, Econometrics 2 for Economics and Finance, Machine Learning for Economic Analysis, Advanced Econometric Methods, Mathematical and Statistical Methods, Environmental Economics, Applied Economics Dissertation, Environmental Research: A Journey Across Disciplines.
Frequently asked questions
What are the entry requirements for MSc Environmental Modelling and Data Analysis?
Entry requirements for MSc Environmental Modelling and Data Analysis at University of Bristol: Upper second-class honours degree or international equivalent in Engineering, Mathematics or a Physical Science subject; non-standard subjects need 60% in a relevant module. Confirm with the university.
What will I study in MSc Environmental Modelling and Data Analysis?
MSc Environmental Modelling and Data Analysis covers areas like data-science, mathematical-economics, statistical-computing, computational-mathematics, data-analytics, quantitative-economics, data-analysis, social-research-methods.
Who offers MSc Environmental Modelling and Data Analysis?
MSc Environmental Modelling and Data Analysis is offered by University of Bristol, England.
Considering MSc Environmental Modelling and Data Analysis?
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Sources: University of Bristol official course page. Information is compiled and summarised — not copied verbatim — and is approximate; always confirm with the original source.
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